Raquel Guiomar

Estimates of Pandemic Influenza Vaccine Effectiveness in Europe, 2009–2010: Results of Influenza Monitoring Vaccine Effectiveness in Europe (I-MOVE) Multicentre Case-Control Study

Results from a European multicentre case-control study reported by Marta Valenciano and colleagues suggest good protection by the pandemic monovalent H1N1 vaccine against pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine on H1N1.

Influenza vaccine effectiveness estimates in Europe in a season with three influenza type/subtypes circulating: the I-MOVE multicentre case–control study, influenza season 2012/13

In the fifth season of Influenza Monitoring Vaccine Effectiveness in Europe (I-MOVE), we undertook a multicentre case-control study (MCCS) in seven European Union (EU) Member States to measure 2012/13 influenza vaccine effectiveness against medically attended influenza-like illness (ILI) laboratory confirmed as influenza. The season was characterised by substantial co-circulation of influenza B, A(H1N1)pdm09 and A(H3N2) viruses. Practitioners systematically selected ILI patients to swab ≤7 days of symptom onset. We compared influenza-positive by type/subtype to influenza-negative patients among those who met the EU ILI case definition. We conducted a complete case analysis using logistic regression with study as fixed effect and calculated adjusted vaccine effectiveness (AVE), controlling for potential confounders (age, sex, symptom onset week and presence of chronic conditions). We calculated AVE by type/subtype. Study sites sent 7,954 ILI/acute respiratory infection records for analysis. After applying exclusion criteria, we included 4,627 ILI patients in the analysis of VE against influenza B (1,937 cases), 3,516 for A(H1N1)pdm09 (1,068 cases) and 3,340 for influenza A(H3N2) (730 cases). AVE was 49.3% (95% confidence interval (CI): 32.4 to 62.0) against influenza B, 50.4% (95% CI: 28.4 to 65.6) against A(H1N1)pdm09 and 42.2% (95% CI: 14.9 to 60.7) against A(H3N2). Our results suggest an overall low to moderate AVE against influenza B, A(H1N1)pdm09 and A(H3N2), between 42 and 50%. In this season with many co-circulating viruses, the high sample size enabled stratified AVE by type/subtype. The low estimates indicate seasonal influenza vaccines should be improved to achieve acceptable protection levels.

Estimates of 2012/13 influenza vaccine effectiveness using the case test-negative control design with different influenza negative control groups

BACKGROUND In recent years several reports of influenza vaccine effectiveness (VE) have been made early for public health decision. The majority of these studies use the case test-negative control design (TND), which has been showed to provide, under certain conditions, unbiased estimates of influenza VE. Nevertheless, discussions have been taken on the best influenza negative control group to use. The present study aims to contribute to the knowledge on this field by comparing influenza VE estimates using three test-negative controls: all influenza negative, non-influenza respiratory virus and pan-negative. METHODS Incident ILI patients were prospectively selected and swabbed by a sample of general practitioners. Cases were ILI patients tested positive for influenza and controls ILI patients tested negative for influenza. The influenza negative control group was divided into non-influenza virus control group and pan-negative control group. Data were collected on vaccination status and confounding factors. Influenza VE was estimated as one minus the odds ratio of been vaccinated in cases versus controls adjusted for confounding effect by logistic regression. RESULTS Confounder adjusted influenza VE against medically attended laboratory-confirmed influenza was 68.4% (95% CI: 20.7-87.4%) using all influenza negatives controls, 82.1% (95% CI: 47.6-93.9%) using non-influenza controls and 49.4% (95% CI: -44.7% to 82.3%) using pan-negative controls. CONCLUSIONS Influenza VE estimates differed according to the influenza negative control group used. These results are in accordance with the expected under the hypothesis of differential viral interference between influenza vaccinated and unvaccinated individuals. Given the wide importance of TND study further studies should be conducted in order to clarify the observed differences.

Hospitalization Risk Due to Respiratory Illness Associated with Genetic Variation at IFITM3 in Patients with Influenza A(H1N1)pdm09 Infection: A Case-Control Study

Background Recent studies suggest an association between the Interferon Inducible Transmembrane 3 (IFITM3) rs12252 variant and the course of influenza infection. However, it is not clear whether the reported association relates to influenza infection severity. The aim of this study was to estimate the hospitalization risk associated with this variant in Influenza Like Illness (ILI) patients during the H1N1 pandemic influenza. Methods A case-control genetic association study was performed, using nasopharyngeal/oropharyngeal swabs collected during the H1N1 pandemic influenza. Laboratory diagnosis of influenza infection was performed by RT-PCR, the IFITM3 rs12252 was genotyped by RFLP and tested for association with hospitalization. Conditional logistic regression was performed to calculate the confounder-adjusted odds ratio of hospitalization associated with IFITM3 rs12252. Results We selected 312 ILI cases and 624 matched non-hospitalized controls. Within ILI Influenza A(H1N1)pdm09 positive patients, no statistical significant association was found between the variant and the hospitalization risk (Adjusted OR: 0.73 (95%CI: 0.33–1.50)). Regarding ILI Influenza A(H1N1)pdm09 negative patients, CT/CC genotype carriers had a higher risk of being hospitalized than patients with TT genotype (Adjusted OR: 2.54 (95%CI: 1.54–4.19)). Conclusions The IFITM3 rs12252 variant was associated with respiratory infection hospitalization but not specifically in patients infected with Influenza A(H1N1)pdm09.

2015/16 I-MOVE/I-MOVE+ multicentre case-control study in Europe: Moderate vaccine effectiveness estimates against influenza A(H1N1)pdm09 and low estimates against lineage-mismatched influenza B among children.

During the 2015/16 influenza season in Europe, the cocirculating influenza viruses were A(H1N1)pdm09 and B/Victoria, which was antigenically distinct from the B/Yamagata component in the trivalent influenza vaccine.

INSaFLU: an automated open web-based bioinformatics suite “from-reads” for influenza whole-genome-sequencing-based surveillance

BackgroundA new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data.ResultsWe developed and implemented INSaFLU (“INSide the FLU”), which is the first influenza-oriented bioinformatics free web-based suite that deals with primary NGS data (reads) towards the automatic generation of the output data that are actually the core first-line “genetic requests” for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants’ annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform multi-step software intensive analyses in a user-friendly manner without previous advanced training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tuned data analysis. This platform additionally flags samples as “putative mixed infections” if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional “consensus-based” influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission.ConclusionsIn summary, INSaFLU supplies public health laboratories and influenza researchers with an open “one size fits all” framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.INSaFLU can be accessed through https://insaflu.insa.pt.

Improving influenza virological surveillance in Europe: strain-based reporting of antigenic and genetic characterisation data, 11 European countries, influenza season 2013/14

Influenza antigenic and genetic characterisation data are crucial for influenza vaccine composition decision making. Previously, aggregate data were reported to the European Centre for Disease Prevention and Control by European Union/European Economic Area (EU/EEA) countries. A system for collecting case-specific influenza antigenic and genetic characterisation data was established for the 2013/14 influenza season. In a pilot study, 11 EU/EEA countries reported through the new mechanism. We demonstrated feasibility of reporting strain-based antigenic and genetic data and ca 10% of influenza virus-positive specimens were selected for further characterisation. Proportions of characterised virus (sub)types were similar to influenza virus circulation levels. The main genetic clades were represented by A/StPetersburg/27/2011(H1N1)pdm09 and A/Texas/50/2012(H3N2). A(H1N1)pdm09 viruses were more prevalent in age groups (by years) < 1 (65%; p = 0.0111), 20–39 (50%; p = 0.0046) and 40–64 (55%; p = 0.00001) while A(H3N2) viruses were most prevalent in those ≥ 65 years (62%*; p = 0.0012). Hospitalised patients in the age groups 6–19 years (67%; p = 0.0494) and ≥ 65 years (52%; p = 0.0005) were more frequently infected by A/Texas/50/2012 A(H3N2)-like viruses compared with hospitalised cases in other age groups. Strain-based reporting enabled deeper understanding of influenza virus circulation among hospitalised patients and substantially improved the reporting of virus characterisation data. Therefore, strain-based reporting of readily available data is recommended to all reporting countries within the EU/EEA.

Respiratory infections in elderly people: Viral role in a resident population of elderly care centers in Lisbon, winter 2013–2014

Abstract Objective The aim of this study was to analyze the etiology and clinical consequences of viral respiratory infections in 18 elderly care centers (ECC) in Lisbon, which housed a total of 1022 residents. Methods Nasopharyngeal swabs were collected whenever an elderly had symptoms of acute respiratory infections (ARI). PCR and RT-PCR were performed for influenza A/B, human parainfluenza virus 1–4, adenovirus, human metapneumovirus (HMPV), respiratory syncytial virus (RSV), rhinovirus, enterovirus, human coronavirus and human Bocavirus (HBoV). Array cards for atypical bacteria were also used in severe cases. Results In total, 188 episodes of ARI were reported, being rhinovirus the most frequently detected (n=53), followed by influenza A(H3) (n=19) and HBoV (n=14). Severe infections were reported in 19 patients, 11 of which were fatal, Legionela pneumophila, rhinovirus, HMPV and RSV associated with these fatalities. Nine influenza strains were analyzed, all antigenically dissimilar from vaccine strain 2013/14. “Age”, “HMPV” and “Respiratory disease” showed an association with severe infection. Conclusions In this study an etiologic agent could be found in 60% of the acute respiratory episodes. These data provides information about the circulating viruses in ECC and highlights the importance of searching both viruses and atypical bacteria in severe ARI.

Cross-protection to new drifted influenza A(H3) viruses and prevalence of protective antibodies to seasonal influenza, during 2014 in Portugal

INTRODUCTION Immune profile for influenza viruses is highly changeable over time. Serological studies can assess the prevalence of influenza, estimate the risk of infection, highlight asymptomatic infection rate and can also provide data on vaccine coverage. The aims of the study were to evaluate pre-existing cross-protection against influenza A(H3) drift viruses and to assess influenza immunity in the Portuguese population. MATERIALS AND METHODS We developed a cross-sectional study based on a convenience sample of 626 sera collected during June 2014, covering all age groups, both gender and all administrative health regions of Portugal. Sera antibody titers for seasonal and new A(H3) drift influenza virus were evaluated by hemagglutination inhibition assay (HI). Seroprevalence to each seasonal influenza vaccine strain virus and to the new A(H3) drift circulating strain was estimated by age group, gender and region and compared with seasonal influenza-like illness (ILI) incidence rates before and after the study period. RESULTS Our findings suggest that seroprevalences of influenza A(H3) (39.9%; 95% CI: 36.2-43.8) and A(H1)pdm09 (29.7%; 95% CI: 26.3-33.4) antibodies were higher than for influenza B, in line with high ILI incidence rates for A(H3) followed by A(H1)pdm09, during 2013/2014 season. Low pre-existing cross-protection against new A(H3) drift viruses were observed in A(H3) seropositive individuals (46%). Both against influenza A(H1)pdm09 and A(H3) seroprotection was highest in younger than 14-years old. Protective antibodies against influenza B were highest in those older than 65years old, especially for B/Yamagata lineage, 33.3% (95% CI: 25.7-41.9). Women showed a high seroprevalence to influenza, although without statistical significance, when compared to men. A significant decreasing trend in seroprotection from north to south regions of Portugal mainland was observed. CONCLUSIONS Our results emphasize that low seroprotection increases the risk of influenza infection in the following winter season. Seroepidemiological studies can inform policy makers on the need for vaccination and additional preventive measures.